No abstract

Chromosome visualization has been used in human chromosome analysis and is a crucial step in clinical diagnosis and drug development. An important step in chromosome visualization is the extraction of chromosomes from chromosome images obtained by light microscopy. Chromosomes often overlap in a complex and variable manner, resulting in significant challenges in chromosome segmentation. The process of chromosome visualization requires manual intervention and is tedious. A method based on a neural network is proposed for the automatic segmentation of overlapping chromosome images to speed up the workflow of visualizing chromosomes. Three improved dilated convolutions are used in the chromosome image segmentation models based on U-Net. The proposed models successfully segment overlapping chromosomes in two publicly available overlapping chromosome data sets. Our models have better performance than existing overlapping chromosome segmentation methods based on U-Net. In summary, it is demonstrated that the improved dilated convolutions can be used for the automatic segmentation of overlapping chromosome images. The proposed improved dilated convolutions have a stable performance improvement, can be easily extended to the segmentation of multiple overlapping chromosomes, and are suitable as general neural network operations to replace standard convolutions in any network.

Abstract. High-resolution sea ice modeling is becoming widely available for both operational forecasts and climate studies. In traditional Eulerian grid-based models, small-scale sea ice kinematics represent the most prominent feature of high-resolution simulations, and with rheology models such as viscous–plastic (VP) and Maxwell elasto-brittle (MEB), sea ice models are able to reproduce multi-fractal sea ice deformation and linear kinematic features that are seen in high-resolution observational datasets. In this study, we carry out modeling of sea ice with multiple grid resolutions by using the Community Earth System Model (CESM) and a grid hierarchy (22, 7.3, and 2.4 km grid stepping in the Arctic). By using atmospherically forced experiments, we simulate consistent sea ice climatology across the three resolutions. Furthermore, the model reproduces reasonable sea ice kinematics, including multi-fractal spatial scaling of sea ice deformation that partially depends on atmospheric circulation patterns and forcings. By using high-resolution runs as references, we evaluate the model's effective resolution with respect to the statistics of sea ice kinematics. Specifically, we find the spatial scale at which the probability density function (PDF) of the scaled sea ice deformation rate of low-resolution runs matches that of high-resolution runs. This critical scale is treated as the effective resolution of the coarse-resolution grid, which is estimated to be about 6 to 7 times the grid's native resolution. We show that in our model, the convergence of the elastic–viscous–plastic (EVP) rheology scheme plays an important role in reproducing reasonable kinematics statistics and, more strikingly, simulates systematically thinner sea ice than the standard, non-convergent experiments in landfast ice regions of the Canadian Arctic Archipelago. Given the wide adoption of EVP and subcycling settings in current models, it highlights the importance of EVP convergence, especially for climate studies and projections. The new grids and the model integration in CESM are openly provided for public use.

Regional ocean models usually utilize orthogonal curvilinear grids that are fit to the coastline of the modeled regions. While the orthogonality of the grid is required from the perspective of the numerical algorithms, the alignment to the irregular coastlines improves the characterization of the land-sea distribution and the ocean simulation. In this article, we carry out fractal analysis of two representative coastal regions and discuss the trade-offs between the orthogonality and coastline alignment during the grid generation of these regions. A new grid generation method based on Schwarz-Christoffel conformal mappings is proposed, with automatic coastal boundary retrieval algorithm that generates resolution dependent boundary for grid generation and alleviates the human efforts involved in traditional methods. We show that for the southeastern Pacific region, the coastline is smooth with low fractal dimension and there exists effective trade-off with a coastline boundary that Center of Earth System Sciences, Tsinghua University, Beijing, 100084, China adjusts to the desired grid resolution. On the contrary, there is no effective trade-off for southeast China seas where the coastline is of higher fractal dimension, and a coarser coastline boundary is recommended for better orthogonality with little loss in coastline alignment. Further numerical study of coastal trapped Kelvin waves for the typical regions demonstrate that the new coastline-fitting grids achieve smaller error in numerical dispersion and higher accuracy. Through analysis, we conclude that for grid generation for regional ocean modeling, modelers should bring into consideration of the multi-scale fractal characteristics of the coastline.